Causality Reading Group

Organizer: Joris Mooij
Time: Friday afternoon, 14:30 - 15:30, if not indicated otherwise
Location: C3.146

Schedule 2016

DateArticleDiscussant
2016/01/08Controlling the False Discovery Rate: A Practical and Powerful Approach to Multiple Testing by Benjamini and HochbergPhilip Versteeg

The schedule for the reading club has moved to the AMLab website.

Schedule 2015

DateArticleDiscussant
2015/01/30Computing Maximum Likelihood Estimates in Recursive Linear Models with Correlated Errors by M. Drton, M. Eichler, T. S. RichardsonNicholas Cornia
2015/02/13Constraint-based Causal Discovery: Conflict Resolution with Answer Set Programming, and supplement, by A. Hyttinen, F. Eberhardt, and M. JärvisaloSara Magliacane
2015/02/20Enriching for direct regulatory targets in perturbed gene-expression profiles by S. G. Tringe, A. Wagner, S. W. RubyPhilip Versteeg
2015/02/27Characterization and Greedy Learning of Interventional Markov Equivalence Classes of Directed Acyclic Graphs by A. Hauser and P. BühlmannJoris Mooij
2015/03/06Causal Discovery from Changes by J. Tian and J. PearlSara Magliacane
2015/03/13Causal Discovery from Changes: a Bayesian Approach by J. Tian and J. PearlPhilip Versteeg
2015/03/20Constraint-based Causal Discovery from Multiple Interventions over Overlapping Variable Sets (pp. 1-12) by S. Triantafillou and I. TsamardinosNicholas Cornia
2015/03/27Constraint-based Causal Discovery from Multiple Interventions over Overlapping Variable Sets (pp. 13-22) by S. Triantafillou and I. TsamardinosPhilip Versteeg
2015/04/16Constraint-based Causal Discovery from Multiple Interventions over Overlapping Variable Sets (pp. 23-47) by S. Triantafillou and I. Tsamardinos; Statistical significance for genomewide studies by J.D. Storey and R. TibshiraniJoris Mooij
2015/06/12Feedback models interpretation and discovery, chapter 2 of PhD thesis of Thomas RichardsonMartin Gullaksen
2015/07/03Advances in Bayesian Network Learning using Integer Programming by Bartlett and CussensSara Magliacane
2015/07/24backShift: Learning causal cyclic graphs from unknown shift interventions by Rothenhäsler, Heinze, Peters, MeinshausenJoris Mooij
2015/07/31Computing Maximum Likelihood Estimates in Recursive Linear Models with Correlated Errors by M. Drton, M. Eichler, and T. S. RichardsonJoris Mooij
2015/08/28Single timepoint models of dynamic systems by K. Sachs, S. Itani, J. Fitzgerald, B. Schoeberl, G.P. Nolan, C.J. TomlinJoris Mooij
2015/09/11UAI tutorial Non-parametric Causal Models by Richardson and Evans (part 1a; slides, video)-
2015/09/18UAI tutorial Non-parametric Causal Models by Richardson and Evans (part 1b; slides, video)-
2015/09/25--
2015/09/30Studies in Causal Reasoning and Learning (ch. 1, 4.1, 4.2, 4.3) by Jin TianJoris Mooij
2015/10/02--
2015/10/09Influence Diagrams by Howard and Matheson & Influence Diagrams - Historical and Personal Perspectives by Pearl & Influence Diagrams for Causal Modelling and Inference by A.P. DawidDiederik Roijers
2015/10/16Distribution-Free Learning of Bayesian Network Structure in Continuous Domains by D. MargaritisSara Magliacane
2015/10/23Graphs for margins of Bayesian networks (without section 6) by R. EvansStephan Bongers
2015/11/06unspecifiedDiederik Roijers
2015/11/13Inferring latent structures via information inequalities by Chaves, Luft, Maciel, Gross, Janzing and SchölkopfPhilip Versteeg
2015/11/30 11:00-12:00Independence Properties of Directed Markov Fields by Lauritzen, Dawid, Larsen, LeimerTBA
2015/12/4--
2015/12/11Single World Intervention Graphs: A Primer by Richardson and RobinsJoris
2015/12/22Single World Intervention Graphs: A Primer by Richardson and RobinsTBA

Schedule 2014

DateArticleDiscussant
2014/05/23Chain graph models and their causal interpretations by S.L. Lauritzen and T.S. RichardsonJoris Mooij
2014/06/13Classification using Discriminative Restricted Boltzmann Machines by H. Larochelle and Y. BengioSergio Mota

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